Study level

  • PhD
  • Master of Philosophy
  • Honours

Faculty/School

Faculty of Engineering

School of Electrical Engineering and Robotics

Topic status

We're looking for students to study this topic.

Research centre

Supervisors

Professor Clinton Fookes
Position
Head of School, Electrical Engineering and Robotics
Division / Faculty
Faculty of Engineering
Dr Leo Lebrat
Position
Senior Research Fellow
Division / Faculty
Faculty of Engineering
Professor Olivier Salvado
Position
Professor in Artificial Intelligence
Division / Faculty
Faculty of Engineering

Overview

New computer vision methods using machine learning can reconstruct 3D dynamic environments. We are working on medical application to track clinicians, patients body, lesions and tools. Those techniques can be applied for tracking injuries (e.g. wound), providing analytic of operating theatre, and provide guidance for  surgical intervention.

Research activities

This project is part of a large activity within a multidisciplinary team in collaboration with clinical and commercial partners. The student will investigate several 3D reconstruction methods and validate results using large datasets.

The main activity will involved coding using Python and the Pytorch machine learning environment. Methods to be explored include neural radiance field, Gaussian splatting, as well as advanced machine learning methods such as diffusion based generative model. The student is expected to contribute to:

  • developing and testing advanced methods in high performance computing environments
  • collaborating with researchers from QUT and clinical partners
  • delivering high-quality research presentations and publications
  • evaluating algorithms with real world data.

Outcomes

The primary outcomes from this project include:

  • data management and organisation
  • Python software implementing advanced machine learning and computer vision methods
  • research papers in top international conferences and journals
  • research presentations at international conferences, academic institutions, and industry.

Skills and experience

To be considered for this project you'll need a high GPA with experience and skills in a number of the following areas:

  • programming (at least Python, Pytorch)
  • algorithms, optimisation
  • machine learning
  • computer vision.

A solid background and interest in physics and/or mathematics will be highly valued.

Scholarships

You may be eligible to apply for a research scholarship.

Explore our research scholarships

Keywords

Contact

Contact Professor Olivier Salvado via email olivier.salvado@qut.edu.au for more information.